We use a regulatory model with resistance evolution in two pests to insecticidal Bt cotton and pyrethroids (a conventional insecticide) to examine non-Bt cotton (refuge) planting requirements designed to manage Bt-resistance evolution in the midsouth. Our analysis suggests that reduced refuge requirements would enhance producer profitability, sprayed refugia are more cost effective than unsprayed refugia, and producers would receive slightly higher returns under dynamic relative to static refuge policies. Pyrethroid susceptibility in one of the pests was a renewable resource, and toxin-mixture effects associated with pyrethroid use in Bt cotton were important considerations for midsouth refuge policies. Copyright 2004, Oxford University Press.
A model for determination of economic thresholds, or minimum weed population densities justifying the use of postemergence herbicide treatment, for five weed species in soybeans [Glycine max(L.) Merr.] is presented. Sensitivity analysis was performed on the model with respect to economic, statistical, and agronomic variables. The model was refined to include uncertainty about lost field days during the spraying period. Predictions from both the simple and refined models were consistent with economic theory. It was also determined that the economic threshold is sensitive to choice of data-collection ranges and functional form in weed-interference studies.
This article examines the potential demand for Bt cotton in the Southeast from information gathered in the first year of commercialization. We combine revealed preference (RP) data on adoption of Bt cotton varieties with stated preference (SP) data on willingness to adopt to estimate demand using a double-bounded maximum likelihood procedure. Using estimated demand equations, we simulate the costs of reducing conventional insecticide applications through subsidization of Bt cotton. Results indicate that reducing cotton insecticide applications by 40% in the Southeast would require a $21/acre subsidy, with total annual program costs between $53 million and $60 million. Copyright 2000, Oxford University Press.
Farmers may value water quality and user safety characteristics of herbicides as they select among products to obtain weed control. Expenditures per application in the U.S. com and soybean herbicide markets are explained by several safety characteristics in addition to market and weed control characteristics. The explicit inclusion of safety characte¡ in the farm decision model indicates that not all safety aspects of pesticide use are external to farmers. Leaching potential and user toxicity are statistically significant, but their elasticities are small relative to broadleaf and grass weed control efficacy.
The pesticide application practices of California peach growers in controlling peach brown‐rot are used to demonstrate how Bayesian decision theory procedures can be used to arrive at optimal crop disease control practices. Subjective probabilities of disease loss intensity are measured and used in the decision model. Information from an analyst (this researcher) is combined with farmers' subjective probabilities of disease loss by means of Bayes' theorem. Optimal pesticide use actions are computed for three different objective functions—maximum subjective expected returns, mean‐standard deviation of returns, and maximum expected returns with a minimum income side condition.
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